Ashley Stirrup

If the idea sounds weak in plain English, don't run the experiment. Arun Bodapati at Twitch sees too many teams skip that gut check. On the show, he pushed PMs, engineers, and data scientists to do the real work before hitting play. Get the enrollment logic right. Write the hypothesis in plain language. Make sure the intervention is genuinely strong. And stop optimizing ahead of the test. You can always tune later. If the intervention reads weak on paper, it won't save itself in production. You're just burning a cycle. What do you check before you hit play?